Project 2: Multi-Omics of high-risk MM

项目2：高风险MM的多组学

• 批准号: 10488664
• 负责人: Esteban Braggio
• 金额: $ 32.16万
• 依托单位: MAYO CLINIC ARIZONA
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10488664
• 关键词: Accounting; Address; Atlases; Automobile Driving; Biological; Blood; Bone Marrow; Caring; Cells; Clinic; Clinical; Clinical Data; Clinical Trials; Clone Cells; Collaborations; Complex; Complex Analysis; Core Facility; DNA; DNA sequencing; Data; Data Analyses; Data Analytics; Data Set; Disease; Disease Outcome; Environment; Epigenetic Process; Event; Evolution; Generations; Genes; Genetic; Genome; Genomics; Goals; Immune; Immuno-Chemotherapy; Immunophenotyping; Individual; Link; Maps; Marrow; Mass Spectrum Analysis; Mononuclear; Multiomic Data; Multiple Myeloma; Mutation; Network-based; Outcome; Pathogenesis; Pathway interactions; Patients; Pattern; Phase II Clinical Trials; Phenotype; Pilot Projects; Population; Positioning Attribute; Process; Proteome; RNA; Relapse; Resistance; Resolution; Resources; Rewards; Role; Sampling; Sampling Studies; Series; Specimen; Technology; Time; Variant; Work; base; biobank; bioinformatics tool; clinical database; clinical phenotype; clinical risk; data integration; data resource; deep learning; design; drug sensitivity; epigenome; experience; gene environment interaction; gene interaction; high risk; high risk population; immunoregulation; improved; insight; lipidome; mRNA sequencing; metabolome; multidisciplinary; multiple omics; neoplastic cell; patient population; personalized approach; repository; response; single cell analysis; therapeutically effective; transcriptome; transcriptomics; translational clinical trial; treatment response; tumor; tumor microenvironment; tumor-immune system interactions; ultra high resolution; whole genome

PROJECT SUMMARY/ABSTRACT While our own extensive studies have confirmed the significant role of the disrupted genome in Multiple Myeloma (MM), they have also re-emphasized the gaps in understanding, and the importance of immune regulation and gene-environment interaction. It is indeed likely that the evolution of MM, both before or during therapy, is the result of a complex interplay of biological perturbations driven by genetic changes and environmental influences. Our past work has also demonstrated that studying small numbers of patients at great depth can be as rewarding for scientific understanding as studies of superficial genomic events in thousands of patients. Thus we will strive to generate the first, longitudinal, translational clinical trial and comprehensive data resource of environmental genetic interactions for the highest-risk MM population. It is these patients who continue to rapidly fail highly effective therapeutics for reasons which are still completely opaque. New and bold approaches using state-of-the-art technology are required to reverse this decades-old lack of progress. Our hypothesis is that analysis of data capturing gene-environment interactions at high resolution will reveal insights into biological pathways influencing MM responsiveness to therapy and subsequent outcomes. First, we will leverage a carefully studied and homogeneously treated high-risk group of “double hit” patients in a Phase 2 clinical trial with large control clinical databases and bio-repositories to derive, for each patient, a detailed map of environmental gene interactions linked to clinical outcome over time. Second, we will perform a series of complex analyses to identify MM-associated changes in and across the genome, transcriptome, epigenome, immune environment, proteome, lipidome and metabolome. Third, we will study these samples at the highest resolution technically feasible today, and seek to define gene-environment interaction changes over time that associate with response to therapy. Finally, high resolution data capturing these interaction changes and clinical response data will be linked to improve our understanding of the mechanisms underlying MM variability among patients in regards to disease outcomes. This comprehensive resource will enable a more individualized approach to clinical surveillance and therapy for MM.

项目总结/摘要 虽然我们自己的广泛研究已经证实了破坏的基因组在多基因组中的重要作用， 骨髓瘤（MM），他们也重新强调了认识上的差距，以及免疫的重要性。 调控和基因-环境相互作用。MM的进化，无论是在之前还是在过程中， 治疗，是由遗传变化驱动的生物扰动的复杂相互作用的结果， 环境影响。我们过去的工作也表明，研究少数患者， 对于科学理解来说，深入研究就像对人类基因组表面事件的研究一样有益。 成千上万的病人。因此，我们将努力产生第一个纵向转化临床试验， 最高风险MM人群的环境遗传相互作用的综合数据资源。是 这些患者由于仍然完全未知的原因，继续快速失败高效治疗 不透明需要使用最先进的技术的新的和大胆的方法来扭转这一数十年的历史。 缺乏进展。 我们的假设是，对高分辨率的基因-环境相互作用数据的分析将揭示 深入了解影响MM对治疗的反应性和后续结局的生物学途径。第一、 我们将利用一个经过仔细研究和均匀治疗的“双重打击”患者的高风险群体， 2期临床试验，使用大型对照临床数据库和生物储存库，为每名患者获得 随着时间的推移，与临床结果相关的环境基因相互作用的详细地图。第二，我们将执行一个 一系列复杂的分析，以确定MM相关的变化和整个基因组，转录组， 表观基因组、免疫环境、蛋白质组、脂质组和代谢组。第三，我们将研究这些样本， 目前技术上可行的最高分辨率，并寻求定义基因-环境相互作用的变化 与治疗反应相关的变化最后，高分辨率数据捕捉这些相互作用 变化和临床反应数据将联系起来，以提高我们对潜在机制的理解。 MM患者在疾病结局方面的变异性。这一全面的资源将使 更个体化的MM临床监测和治疗方法。